Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.).
Development and use of genic molecular markers (GMMs) for construction of a transcript map of chickpea (Cicer arietinum L.).
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DOI：
10.1007/s00122-011-1556-1
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发表时间：
2011-05
影响因子：
5.4
通讯作者：
Varshney, Rajeev K.
中科院分区：
文献类型：
--
作者：
Gujaria, Neha;Kumar, Ashish;Dauthal, Preeti;Dubey, Anuja;Hiremath, Pavana;Prakash, A. Bhanu;Farmer, Andrew;Bhide, Mangla;Shah, Trushar;Gaur, Pooran M.;Upadhyaya, Hari D.;Bhatia, Sabhyata;Cook, Douglas R.;May, Greg D.;Varshney, Rajeev K.
通过单核苷酸多态性（SNP）、基因微卫星或简单序列重复（SSR）和内含子跨越区（ISR）标记等基因分子标记的开发和整合，构建了鹰嘴豆（世界第三大食用豆类作物和印度第一大食用豆类作物）种间作图群体的转录图谱。为了通过等位基因重测序发现SNP，为鹰嘴豆的688个基因/表达序列标签（EST）和鹰嘴豆的密切相关物种的657个基因/EST设计引物对。对9种鹰嘴豆的2-20个基因型的2-20个候选基因区域进行了高质量的序列分析，获得了1,893个SNP位点，平均频率为1/35.83 bp，多态信息含量（PIC）为0.34。平均2.9个单倍型存在于220个候选基因区域中，平均单倍型多样性为0.6326。如上所述，对220个序列比对的SNP 2CAPS分析总共提供了192个CAPS候选者。对这192个CAPS候选者以及早期通过EST的计算机挖掘确定的87个CAPS候选者的实验分析在173个（62.01%）病例中提供了可评分的扩增，其中预测的测定在143个（82.66%）病例中得到验证（CGMM）。利用鹰嘴豆单基因与蒺藜苜蓿基因组的比对，开发了121个内含子跨越区（CISR）标记，其中87个产生了可评分的产物。此外，对77个EST衍生SSR标记（ICCeM）进行了优化，得到了51个可评分标记。在3个作图群体的5个亲本基因型上筛选出281个易测标记，包括143个CGR、87个CISR和51个ICCeM，共鉴定出104个多态性标记，其中种间作图群体多态性标记90个。其中62个GMM标记与218个已发表的标记（包括64个GMM位点）和20个未发表的标记一起可以整合到该遗传图谱中。因此，在这里建立的遗传图谱，共有300个座位，其中包括126个GMM座位和跨度766.56 cM，平均标记间距离为2.55 cM。总之，这是第一次报告的发展，大规模的基因标记，包括发展易于检测的标记和鹰嘴豆的转录图谱。这些资源不仅可用于鹰嘴豆的基因组分析和遗传育种应用，而且可用于比较豆类基因组学。本文的在线版本（doi：10.1007/s 00122 -011-1556-1）包含补充材料，可供授权用户使用。
A transcript map has been constructed by the development and integration of genic molecular markers (GMMs) including single nucleotide polymorphism (SNP), genic microsatellite or simple sequence repeat (SSR) and intron spanning region (ISR)-based markers, on an inter-specific mapping population of chickpea, the third food legume crop of the world and the first food legume crop of India. For SNP discovery through allele re-sequencing, primer pairs were designed for 688 genes/expressed sequence tags (ESTs) of chickpea and 657 genes/ESTs of closely related species of chickpea. High-quality sequence data obtained for 220 candidate genic regions on 2–20 genotypes representing 9 Cicer species provided 1,893 SNPs with an average frequency of 1/35.83 bp and 0.34 PIC (polymorphism information content) value. On an average 2.9 haplotypes were present in 220 candidate genic regions with an average haplotype diversity of 0.6326. SNP2CAPS analysis of 220 sequence alignments, as mentioned above, provided a total of 192 CAPS candidates. Experimental analysis of these 192 CAPS candidates together with 87 CAPS candidates identified earlier through in silico mining of ESTs provided scorable amplification in 173 (62.01%) cases of which predicted assays were validated in 143 (82.66%) cases (CGMM). Alignments of chickpea unigenes with Medicago truncatula genome were used to develop 121 intron spanning region (CISR) markers of which 87 yielded scorable products. In addition, optimization of 77 EST-derived SSR (ICCeM) markers provided 51 scorable markers. Screening of easily assayable 281 markers including 143 CGMMs, 87 CISRs and 51 ICCeMs on 5 parental genotypes of three mapping populations identified 104 polymorphic markers including 90 markers on the inter-specific mapping population. Sixty-two of these GMMs together with 218 earlier published markers (including 64 GMM loci) and 20 other unpublished markers could be integrated into this genetic map. A genetic map developed here, therefore, has a total of 300 loci including 126 GMM loci and spans 766.56 cM, with an average inter-marker distance of 2.55 cM. In summary, this is the first report on the development of large-scale genic markers including development of easily assayable markers and a transcript map of chickpea. These resources should be useful not only for genome analysis and genetics and breeding applications of chickpea, but also for comparative legume genomics. The online version of this article (doi:10.1007/s00122-011-1556-1) contains supplementary material, which is available to authorized users.
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影响因子：
3.1
作者：
Pfaff, T;Kahl, G
通讯作者：
Kahl, G
DOI：
10.1101/sqb.2003.68.69
发表时间：
2003-01-01
期刊：
COLD SPRING HARBOR SYMPOSIA ON QUANTITATIVE BIOLOGY
影响因子：
--
作者：
Fan, JB;Oliphant, A;Chee, MS
通讯作者：
Chee, MS
影响因子：
3.1
作者：
Hüttel, B;Winter, P;Kahl, G
通讯作者：
Kahl, G
影响因子：
4.2
作者：
Gaitan-Solis, E.;Choi, I. -Y.;Tohme, J.
通讯作者：
Tohme, J.
影响因子：
5.3
作者：
Cuc, Luu M.;Mace, Emma S.;Crouch, Jonathan H.;Quang, Vu D.;Long, Tran D.;Varshney, Rajeev K.
通讯作者：
Varshney, Rajeev K.